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Author Yulhendri, Y., Melati, I., Marna, J., & Softazia
Title The Analysis of the Economic Inequality of the Coast Regions Type Journal Article
Year 2020 Publication (up) Economics Development Analysis Journal Abbreviated Journal
Volume 9 Issue 1 Pages 111-124
Keywords Remote Sensing
Abstract West and East coast of Sumatra are two different geographical and trade routes. The West Coast is connected with trade direction to India, Arabia and Africa while on the East Coast it is connected with trade in the Malacca Strait, East Asian economy. Based on photos of satellite images at night, the east coast has more light compared to the west coast. This study analyzed the differences in economic inequality between the economy of the population residing in the West Coast Region and the East Coast of Sumatra. This study took data sourced from the Indonesian Central Statistics Agency published in the last 5 years, 2013-2017. The data were processed using SPSS and Excel using the Williamson Index analysis tool. There are 23 Regencies / Cities in the West Coast and 23 Regencies / Cities in the East Coast analyzed where the West Coast average growth rate in the last 5 years is 5.17% and East Coast 5.48% with the Inequality index using the Williamson Index formula in West Coast 0.37 and East Coast 0.28. It was found that economic activity on the East Coast tends

to be more lively and higher economic growth with a low level of inequality compared to the West coast of Sumatra
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Call Number IDA @ intern @ Serial 2960
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Author Lopez-Ruiz, H., Nezamuddin, N., Al Hassan, R., & Muhsen, A.
Title Estimating Freight Transport Activity Using Nighttime Lights Satellite Data in China, India and Saudi Arabia Type Journal Article
Year 2019 Publication (up) EconPapers Abbreviated Journal
Volume ks--2019-mp07 Issue Pages
Keywords Remote Sensing; Freight; shipping; freight transport activity; FTA; China; India; Saudi Arabia; Transportation; nighttime lights; NTL
Abstract This paper focuses on the methodology for estimating total freight transport activity (FTA) for three countries — China, India and Saudi Arabia — with the objective of building on current state-of-the-art transportation modeling in three key areas: Studying the relationship between nighttime lights (NTL) and FTA allows for an estimation of full transportation datasets for countries where only a few observation points exist or where data is unavailable. Establishing the foundation for future work on how to use this approach in transport flow estimation (origin-destination matrices). Determining whether this approach can be used globally, given the coverage of the satellite data used. The paper uses the KAPSARC Transport Analysis Framework (KTAF), which estimates transport activity from freely available global data sources, satellite images and NTL. It is a tool for estimating freight transport activity that can be used in models to measure the impact of an accelerated transport policy planning approach. The methodology offers a solution to inadequate data access and allows for scenario building in policy planning for transportation. This approach allows for quick estimation of the effects of policy measures and economic changes on transportation activities at a global level. The paper also includes a detailed guide on how to replicate the methodology used in this analysis.
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Notes Approved no
Call Number IDA @ intern @ Serial 2639
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Author Falchetta, G.; Noussan, M.
Title Interannual Variation in Night-Time Light Radiance Predicts Changes in National Electricity Consumption Conditional on Income-Level and Region Type Journal Article
Year 2019 Publication (up) Energies Abbreviated Journal Energies
Volume 12 Issue 3 Pages 456
Keywords Remote Sensing; Energy
Abstract Using remotely-sensed Suomi National Polar-orbiting Partnership (NPP)-VIIRS (Visible Infrared Imagery Radiometer Suite) night-time light (NTL) imagery between 2012 and 2016 and electricity consumption data from the IEA World Energy Balance database, we assemble a five-year panel dataset to evaluate if and to what extent NTL data are able to capture interannual changes in electricity consumption within different countries worldwide. We analyze the strength of the relationship both across World Bank income categories and between regional clusters, and we evaluate the heterogeneity of the link for different sectors of consumption. Our results show that interannual variation in nighttime light radiance is an effective proxy for predicting within-country changes in power consumption across all sectors, but only in lower-middle income countries. The result is robust to different econometric specifications. We discuss the key reasons behind this finding. The regions of Sub-Saharan Africa, Middle-East and North Africa, Latin America and the Caribbeans, and East Asia and the Pacific render a significant outcome, while changes in Europe, North America and South Asia are not successfully predicted by NTL. The designed methodological steps to process the raw data and the findings of the analysis improve the design and application of predictive models for electricity consumption based on NTL at different spatio-temporal scales.
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ISSN 1996-1073 ISBN Medium
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Notes Approved no
Call Number GFZ @ kyba @ Serial 2200
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Author Jasiński, T.
Title Modeling electricity consumption using nighttime light images and artificial neural networks Type Journal Article
Year 2019 Publication (up) Energy Abbreviated Journal Energy
Volume 179 Issue Pages 831-842
Keywords Remote Sensing
Abstract The purpose of this paper is to model electricity consumption using Artificial Neural Networks (ANN). Total electricity consumption and consumption generated by households (HH) were modeled. The input variables of the ANN were based on nighttime light images from VIIRS DNB. Studies conducted thus far have covered mainly linear models. Most of case studies focused on single countries or groups of countries with only few focusing on the sub-national scale. This paper is pioneering in covering an area of Poland (Central Europe) at NUTS-2 level. The use of ANN enabled the modeling of the non-linear relations associated with the complex structure of electricity demand. Satellite data were collected for the period 2013–2016, and included images with improved quality (inter alia higher resolution), compared to the DMSP/OLS program. As images are available from April 2012 onwards, it is only recently that their number has become sufficient for ANN learning. The images were used to create models of multilayer perceptrons. The results achieved by ANN were compared with the results obtained using linear regressions. Studies have confirmed that electricity consumption can be determined with higher precision by the ANN method.
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ISSN 0360-5442 ISBN Medium
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Notes Approved no
Call Number GFZ @ kyba @ Serial 2475
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Author Shi, K.; Yu, B.; Huang, C.; Wu, J.; Sun, X.
Title Exploring spatiotemporal patterns of electric power consumption in countries along the Belt and Road Type Journal Article
Year 2018 Publication (up) Energy Abbreviated Journal Energy
Volume 150 Issue Pages 847-859
Keywords Remote Sensing
Abstract Fully understanding spatiotemporal patterns of electric power consumption (EPC) is one of the key questions related to sustainable socioeconomic and environmental development in countries along the Silk Road Economic Belt and the 21st-Century Maritime Silk Road (hereinafter referred to as the Belt and Road countries). However, studies about spatiotemporal patterns of EPC in the Belt and Road countries are still scarce due to the lack of reliable data. This study attempted to investigate spatiotemporal patterns of EPC in the Belt and Road countries from multiple perspectives. Firstly, the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime stable light data were used to estimate EPC from 1992 to 2013. Subsequently, the mathematical statistic method, standard deviational ellipse, rank size rule, and correlation analysis were employed to evaluate the EPC change in detail. The results reveal that the EPC growth mainly occurs in the developing countries, especially in China. The geographical distribution of EPC in the Belt and Road countries is oriented in the Northwest-Southeast direction between 1992 and 2013. Based on the rank size rule analysis, the slope values of q are −2.392 and −2.175 between 1992 and 2013, with an average R2 value of 0.664, indicating a clear clustering pattern of EPC. It is also proved that GDP is a more important impact factor to EPC than the population. Our findings can offer an effective way to understand spatiotemporal evolution characteristics of EPC in the Belt and Road countries, and provide references for regional socioeconomic development and cooperation.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0360-5442 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2487
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